optuna.integration¶

AllenNLP¶

`optuna.integration.AllenNLPExecutor`	AllenNLP extension to use optuna with Jsonnet config file.
`optuna.integration.allennlp.dump_best_config`	Save JSON config file after updating with parameters from the best trial in the study.
`optuna.integration.AllenNLPPruningCallback`	AllenNLP callback to prune unpromising trials.

Catalyst callback to prune unpromising trials.

`optuna.integration.ChainerPruningExtension`	Chainer extension to prune unpromising trials.
`optuna.integration.ChainerMNStudy`	A wrapper of `Study` to incorporate Optuna with ChainerMN.

FastAI callback to prune unpromising trials for fastai.

Keras callback to prune unpromising trials.

`optuna.integration.LightGBMPruningCallback`	Callback for LightGBM to prune unpromising trials.
`optuna.integration.lightgbm.train`	Wrapper of LightGBM Training API to tune hyperparameters.
`optuna.integration.lightgbm.LightGBMTuner`	Hyperparameter tuner for LightGBM.
`optuna.integration.lightgbm.LightGBMTunerCV`	Hyperparameter tuner for LightGBM with cross-validation.

Callback to track Optuna trials with MLflow.

MXNet callback to prune unpromising trials.

`optuna.integration.PyCmaSampler`	A Sampler using cma library as the backend.
`optuna.integration.CmaEsSampler`	Wrapper class of PyCmaSampler for backward compatibility.

`optuna.integration.PyTorchIgnitePruningHandler`	PyTorch Ignite handler to prune unpromising trials.
`optuna.integration.PyTorchLightningPruningCallback`	PyTorch Lightning callback to prune unpromising trials.

Hyperparameter search with cross-validation.

Sampler using Scikit-Optimize as the backend.

Skorch callback to prune unpromising trials.

`optuna.integration.TensorBoardCallback`	Callback to track Optuna trials with TensorBoard.
`optuna.integration.TensorFlowPruningHook`	TensorFlow SessionRunHook to prune unpromising trials.
`optuna.integration.TFKerasPruningCallback`	tf.keras callback to prune unpromising trials.

Callback for XGBoost to prune unpromising trials.